{"id":"W7146937138","doi":"10.1145/3769872.3769886","title":"SenseSync: Supporting Collaborative Information-Seeking with the Involvement of Large Language Models","year":2025,"lang":"","type":"article","venue":"","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Timeline; Summative assessment; Formative assessment; Work (physics); Visual language; Affordance; Collaborative software","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00814646,0.00185972,0.0008604246,0.001501963,0.0009648684,0.002712772,0.002714076,0.001511902,0.007695021],"category_scores_gemma":[0.03360502,0.0009421392,0.001261961,0.0005797155,0.001447763,0.006197805,0.009683536,0.001904194,0.002088255],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008275286,"about_ca_system_score_gemma":0.002550819,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002996566,"about_ca_topic_score_gemma":0.006794979,"domain_scores_codex":[0.9933941,0.004203092,0.0004147095,0.0008515014,0.0009249533,0.0002115969],"domain_scores_gemma":[0.966352,0.02867149,0.0007871687,0.002325026,0.0009606609,0.0009036673],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.005062138,0.001742698,0.01406284,0.006847087,0.0007850103,0.004008145,0.04976142,0.03459898,0.1109245,0.06801192,0.07779166,0.6264035],"study_design_scores_gemma":[0.001026824,0.00149539,0.004364736,0.0009411443,0.0004510013,0.001915502,0.008120982,0.5865329,0.06210499,0.07915409,0.2531344,0.0007581552],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0815552,0.0007221891,0.8161253,0.001287159,0.0002244375,0.001442439,0.002581365,0.08743521,0.008626772],"genre_scores_gemma":[0.3097722,0.0003076365,0.6730949,0.0005681315,0.00006831834,0.001884444,0.003906984,0.003705511,0.006691863],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00814646,"threshold_uncertainty_score":0.04308313,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04918592044545994,"score_gpt":0.3986674052027017,"score_spread":0.3494814847572418,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}